find how many times and which columns a string is repeated - r

Question

My data consists of 6 strings per each element. It has string with 6 characters. The data has white space too.
I want to know how many times each string is repeated in all columns
for example P67809 is repeated 2 times in column a and column d
so the output should look likes
string No columns
P67809 2 a,b
Based on this function I can assign a row number to each string
normalize <- function(x, delim) {
x <- gsub(")", "", x, fixed=TRUE)
x <- gsub("(", "", x, fixed=TRUE)
idx <- rep(seq_len(length(x)), times=nchar(gsub(sprintf("[^%s]",delim), "", as.character(x)))+1)
names <- unlist(strsplit(as.character(x), delim))
return(setNames(idx, names))
}
Then I apply the function on all and each columns string like
myS <- lapply(mydata, normalize,";")
but I don't know how to then search and get the output

Answer 1

We could melt the data from 'wide' to 'long' format. Split the 'value' column with ; to get a list output. We set the names of the list as the 'variable' column of 'dM'. Then stack the list to a two column output, and get the frequency count with 'tbl'. It may be easier to understand the result from the 'tbl' output.
library(reshape2)
dM <- melt(mydata, id.var=NULL)
lst1 <- setNames(strsplit(dM$value, ";"), dM$variable)
tbl <- table(stack(lst1)[2:1])
tbl
values
#ind A4QPH2 O60814 P0CG47 P0CG48 P14923 P15924 P19338 P35908 P42356 P57053 P58876 P62750 P62807 P62851 P62979 P63241 P67809 Q02413 Q06830 Q07955 Q16658 Q5QNW6 Q6IS14 Q8N8J0 Q93079 Q969S3
# a 0 1 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
# b 3 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 1 0 0 0
# c 1 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 1 0 1 0 0 0
# d 0 0 1 1 1 0 0 0 0 0 1 1 1 1 0 1 0 1 0 1 1 0 1 0 0 1 1
# values
#ind Q99877 Q99879 Q9Y2T7
# a 0 0 1
# b 0 0 0
# c 0 0 0
# d 1 1 1
We get the total number of each element with colSums.
cS <- colSums(tbl)
If we need to get the output as in the OP's post, we can melt the list output to create a 2 column data.frame. From this, we convert to 'data.table' (setDT(), grouped by 'value' column , we get the length of unique elements of 'variable' and also paste together the unique elements.
library(data.table)
res <- setDT(melt(lst1))[, list(No= uniqueN(L1),
columns= toString(unique(L1))) ,.(string=value)]
head(res,2)
# string No columns
#1: P67809 2 a, d
#2: Q9Y2T7 2 a, d

Answer 2

One approach might be:
res <- apply(mydata, 2, function(x) unlist(strsplit(x, ";")))
un <- unique(unlist(res))
res2 <- sapply(un, function(x) lapply(res, function(y) as.numeric(x %in% y)))
res2
P67809 Q9Y2T7 P42356 Q8N8J0 A4QPH2 P35908 P19338 P15924 P14923 Q02413 P63241 Q6IS14
a 1 1 1 1 1 1 1 1 1 0 0 0
b 0 0 0 0 0 0 0 0 0 1 1 1
c 0 0 0 0 0 0 0 0 0 1 1 1
d 1 1 0 0 0 0 0 0 0 0 0 0
P62979 P0CG47 P0CG48 Q16658 P62851 Q07955 Q06830 P62807 O60814 P57053 Q99879 Q99877
a 0 0 0 0 0 0 0 0 0 0 0 0 0
b 1 1 1 1 0 0 0 0 0 0 0 0 0
c 1 1 1 1 1 1 0 0 0 0 0 0 0
d 1 1 1 0 0 0 1 1 1 1 1 1 1
Q93079 Q5QNW6 P58876 P62750 Q969S3
a 0 0 0 0 0
b 0 0 0 0 0
c 0 0 0 0 0
d 1 1 1 1 1
as.data.frame(t(apply(t(res2), 1, function(x) cbind(sum(as.numeric(x)), paste(names(x)[which(as.logical(x))], collapse = ",")))))
V1 V2
P67809 2 a,d
Q9Y2T7 2 a,d
P42356 1 a
Q8N8J0 1 a
A4QPH2 1 a
P35908 1 a
P19338 1 a
P15924 1 a
P14923 1 a
Q02413 2 b,c
P63241 2 b,c
Q6IS14 2 b,c
P62979 3 b,c,d
P0CG47 3 b,c,d
P0CG48 3 b,c,d
2 b,c
Q16658 1 c
P62851 1 c
Q07955 1 d
Q06830 1 d
P62807 1 d
O60814 1 d
P57053 1 d
Q99879 1 d
Q99877 1 d
Q93079 1 d
Q5QNW6 1 d
P58876 1 d
P62750 1 d
Q969S3 1 d

Answer 3

An alternative approach with cSplit from splitstackshape and gather from tidyr.
library(splitstackshape)
library(tidyr)
library(dplyr)
splitted <- cSplit(mydata, splitCols = names(mydata), sep = ";") %>% gather() # Split cols and melt data
splitted$key <- substring(splitted$key, 1, 1) # Lose irrelevant string
table(splitted) # Generate frequency table